{"id":1374278,"url":"https://alion.io/job/hipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning","title":"Post-Doctoral Researcher F/M Dynamic Parallelization of Sparse Codes for High-Performance Computing and Machine Learning","company":{"id":1803494,"name":"HiPEAC","domain":"hipeac.net","url":"https://alion.io/company/hipeac","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":74,"open_postings":25,"ghost_share":0.52,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":21,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Lyon, France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":48000,"max_usd":103000,"period":"year","method":"role_country_seniority_unknown","sample_n":107},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false}],"status":"live","first_seen_at":"2026-09-16T15:28:44Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-10-19T01:00:42Z","board_verified":true,"closed_at":null,"days_open":32,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":31},"description":"HiPEAC Context & Goals\nMost kernels of interest in machine learning and high-performance computing manipulate sparse tensors. Sparse codes are highly irregular and make use of array indirections and dynamic control which jeopardize static automatic parallelization algorithms.\nThe overall objective of this postdoctoral fellowship is to investigate compiler and runtime algorithms to delay the specialization of the dense code at runtime when the sparse structure is known.\nFrom a dense specification, we seek to compile a code able to specialize itself on the sparse input data. The specialization will involve a set of sub-computations, which are expected to be achievable by standard linear algebra routines (e.g. gemm), using state-of-the art linear algebra libraries.\nSeveral issues must be investigated:\nHow to specialize the code? In particular, how propagate efficiently the sparsity along the computation flow?\nHow to detect library kernels on the specialized code?\nHow to enforce a proper scheduling for the parallel runtime?\nPoints 1 and 2 have been partially addressed by a PhD student.\nThe postdoctoral fellow will:\nPropose code optimizations and data structures for scaling sparse propagation (point 1)\nAddress runtime scheduling (point 3) by relying on existing parallel runtimes\nValidate the complete approach (points 1, 2 and 3) on scientific benchmarks by using sparse tensors from the Florida sparse matrix collection as well as machine learning applications.\nEnvironment & Salary\nThis position is funded by the French prioritary research program for exascale computing in France (PEPR NumPEx).\nThis postdoctoral fellowship will last 14 months and be held at Laboratoire de l’Informatique du Parallélisme at Ecole Normale Supérieure de Lyon, France.\nThe gross salary is 2788 euros/month.\nApply at :https://jobs.inria.fr/public/classic/en/offres/2026-10485\nAbout\nInria Lyon\nInria Lyon is a leading research center in computer science and applied mathematics, dedicated to advancing knowledge and technology. We foster innovation, collaboration, and excellence in research and education.\nMetadata\nTopics: Compilation, High-performance computing, Optimization, Parallel computing, Performance engineering, Runtime performance\nSummary\nInria Lyon seeks a Post-Doctoral Researcher for 14 months to optimize dynamic parallelization of sparse codes in high-performance computing and machine learning, focusing on compiler algorithms and scheduling.\nExternal links\nhttps://jobs.inria.fr/public/classic/en/offres/20…","description_format":"text","description_chars":2525,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["E-learning","Virtual Events"],"lifecycle":[{"event":"open","at":"2026-09-28T06:00:15Z"}],"visa":[],"liveness":{"score":20,"band":"cold","label":"Long shot","p_open":1,"p_active":0.367,"p_room":0.55,"age_days":30,"expected_fill_days":21,"reasons":["conf:1","stale_co","velocity","win:tail"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/hipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning","json_url":"https://alion.io/job/hipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning.json","meta":{"generated_at":"2026-10-19T03:56:31Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":2184,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-20T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1803494},"rest":"https://alion.io/mcp/rest/get_company?id=1803494"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fhipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fhipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fhipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/hipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fhipeac-post-doctoral-researcher-fm-dynamic-parallelization-of-sparse-codes-for-high-performance-computing-and-machine-learning"}]}